ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

ScaleOut Software

APRIL 3, 2020

This software can simultaneously perform these actions for hundreds of thousands of ventilators to keep this vital logistical information instantly available for real-time analysis. These questions can be answered using the latest data as it streams in from the field.

Logistics 52

Logistics Analytics Scalability Cloud 52

Scalegrid

FEBRUARY 8, 2024

At its core, a distributed storage system comprises three main components: a controller for managing the system’s operations, an internal datastore where information is held, and databases geared towards ensuring scalability, partitioning capabilities, and high availability for all types of data.

Storage 130

Storage Systems Big Data Azure 130

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. For testing purposes, usually, a mix of static and dynamic data is needed. Copy production data i.

Testing 60

Testing Storage Database Processing 60

All Things Distributed

JULY 11, 2011

Spot Instances are ideal for use cases like web and data crawling, financial analysis, grid computing, media transcoding, scientific research, and batch processing. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Job Openings in AWS - Senior Leader in Database Services.

AWS 85

AWS Storage Cloud Big Data 85

The Netflix TechBlog

JULY 26, 2021

Such a paradigm aspires to assist front-line operations personnel and stakeholders in “running the business”²; performing their tasks through means such as ad hoc analysis, decision-support, and tracking (of tasks, assets, schedules, etc). In the initial stage, data consumers set up ETL pipelines directly pulling data from databases.

Big Data 253

Big Data Government Analytics Processing 253

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

All Things Distributed

OCTOBER 7, 2015

We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps. In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data.

Cloud 137

Cloud Big Data AWS Analytics 137

All Things Distributed

DECEMBER 13, 2009

These can be incidental tasks, such as the analysis of a particular dataset, or tasks where the amount of work to be done is almost never finished, such as media conversion from a Hollywoods studios movie vault, or web crawling for a search indexing company. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications.

Cloud 63

Cloud AWS Storage Innovation 63

The Morning Paper

SEPTEMBER 19, 2019

MongoDB is an important database, and this paper explains the tunable (per-operation) consistency models that MongoDB provides and how they are implemented under the covers. Microsoft have a paper describing their new recovery mechanism in Azure SQL Database , the key feature being that it can recovery in constant time.

Blockchain 46

Blockchain Hardware Google Analytics 46

Highly Scalable

MARCH 10, 2015

Retail is one of the most important business domains for data science and data mining applications because of its prolific data and numerous optimization problems such as optimal prices, discounts, recommendations, and stock levels that can be solved using data analysis methods. In that case, the equation (1.2)

Retail 152

Retail C++ Analytics Metrics 152

All Things Distributed

DECEMBER 9, 2010

By supporting such large object sizes, Amazon S3 better enables a variety of interesting big data use cases. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Job Openings in AWS - Senior Leader in Database Services. Driving down the cost of Big-Data analytics.

AWS 80

AWS Big Data Scalability Storage 80

All Things Distributed

NOVEMBER 15, 2016

The cost and complexity to implement, scale, and use BI makes it difficult for most companies to make data analysis ubiquitous across their organizations. QuickSight is a cloud-powered BI service built from the ground up to address the big data challenges around speed, complexity, and cost. Enter Amazon QuickSight.

Analytics 152

Analytics Availability Media Social Media 152

All Things Distributed

NOVEMBER 15, 2010

Starting today Amazon EMR can take advantage of the Cluster Compute and Cluster GPU instances, giving customers ever more powerful components to base the large scale data processing and analysis on. a Fast and Scalable NoSQL Database Service Designed for Internet Scale Applications. Driving down the cost of Big-Data analytics.

AWS 136

AWS Latency Programming Architecture 136

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. This information can be a mix of analytical (OLAP) queries (i.e. Inserts are efficient for bulk inserts only.

Database 40

Database Analytics Blockchain Healthcare 40